The continuing decrease in the minimum feature size of modern complementary metal-oxide-semiconductor processes has necessitated a reduction in the circuit supply voltage for reliability and power-dissipation reasons. This reduction is problematic for traditional analog-to-digital conversion schemes because of the reduction in the resolution available within the amplitude range. On the other hand, the decrease in the minimum feature size has a beneficial effect on the obtainable time resolution in the circuitry, owing to the increase in the intrinsic speed of the transistors. Therefore, it is of interest to turn over the amplitude axis to the time axis and to encode information in the latter rather than the former (Roza, IEEE Transactions on Circuits and Systems—II: Analog and Digital Signal Processing, Vol. 44, No. 11, 1997). Such a concept is now known as “time encoding.”
Time encoding is a real-time, asynchronous mechanism for encoding the amplitude information of an analog band-limited signal into a time sequence, or time codes, based on which the signal can be reconstructed. Time codes can be generated by simple non-linear asynchronous analog circuits with low power consumption.
As described in Lazar and Tóth (IEEE Transactions on Circuits and Systems—I: Regular Papers, Vol. 51, No. 10, 2004), which is hereby incorporated by reference, time encoding of a band-limited function x(t) is a representation of x(t) as a sequence of strictly increasing times tk. Alternatively, the output of an encoder can be a digital signal that switches between two values ±b at times tk.
There are two natural requirements that a time-encoding mechanism has to satisfy (Lazar and Tóth, 2004). The first is that the encoding should be implemented as a real-time asynchronous circuit. Second, the encoding mechanism should be invertible, i.e., the amplitude information can be recovered from the time sequence with arbitrary accuracy.
Radio-frequency, or RF, signals are electromagnetic signals, i.e. waveforms with electrical and magnetic properties within the electromagnetic spectrum normally associated with radio wave propagation. Many communication systems modulate electromagnetic signals from baseband to higher frequencies for transmission, and subsequently demodulate those high frequencies back to their original frequency band when they reach the receiver. The original (or baseband) signal may be, for example, data, voice or video. These baseband signals may be produced by transducers such as microphones or video cameras, may be computer-generated, or may be transferred from an electronic storage device. In general, the high frequencies provide longer range and higher-capacity channels than baseband signals, and because high-frequency signals can effectively propagate through the air, they can be used for wireless transmissions as well as hard-wired or wave-guided channels.
While analog communications use a continuously varying signal, a digital transmission can be broken down into discrete messages. Transmitting data in discrete messages allows for greater signal-processing capability. The ability to process a communications signal means that errors caused by random processes can be detected and corrected. Digital signals can also be sampled instead of continuously monitored and multiple signals can be multiplexed together to form one signal. Recent advances in wideband communication channels and solid-state electronics have encouraged applications that utilize digital communications to grow quickly.
Many challenging information applications require high-capacity digital communication links. These applications include bandwidth-efficient RF communication, Low Probability of Intercept and Detection communication, and wide-bandwidth optical communication. Agility in transmission spectral efficiency, as well as spectrally agile transmission capability, is important for free-space optical links in maintaining optimum information capacity, security, network robustness, and power management performance in dynamically changing network environments.
In Lazar and Tóth, IEEE Transactions on Circuits and Systems—I: Regular Papers, Vol. 51, No. 10, 2004, a time-encoding circuit (limit cycle oscillator) is presented to time encode analog band-limited signals. It is shown that an analog input signal can be converted into an asynchronous pulse sequence, and that the original analog input signal can perfectly be recovered from the pulse sequence. However, this disclosure is limited to the time-encoding transformation from the analog domain to the asynchronous pulse domain and back. No attempt is made to time encode digital data and signals. Also, the authors did not attempt to apply the time-encoding circuit to analog-to-digital conversion and to a digital communications link.
In Roza, IEEE Transactions on Circuits and Systems—II: Analog and Digital Signal Processing, Vol. 44, No. 11, 1997, a duty cycle Analog-to-Digital Converter (ADC) architecture is studied. The conversion from the time-encoded analog input signal (asynchronous pulse sequence) to the digital representation of the input signal is done, as described therein, by a direct sampling process. This sampling process introduces large quantization errors that can only be mitigated by significantly over-sampling the individual pulses in the asynchronous pulse sequence. A high-speed and highly accurate external synchronous clock are necessary as described therein. The speed of the clocked sampling circuitry must be much higher than the input signal bandwidth, typically by several orders of magnitude. This seriously limits the achievable bandwidth of the ADC even when it is implemented by state-of-the-art circuit technology (such as is described in R. Walden, “Analog-to-Digital Converter Survey and Analysis,” IEEE Journal on Selected Areas in Communications, Vol. 17, No. 4, 1999). Roza (1997) is further limited to applying the time-encoding concept to analog-to-digital conversion using direct serial sampling of the resultant asynchronous pulse sequence. This method requires a large oversampling ratio in the clocked sampling circuit or the use of poly-phase samplers.
In view of the state of the art, methods and systems are needed that provide digital communication links with high information capacity, such as 50, 100, or more gigabits per second. What would be especially useful is a digital communication architecture based upon the concept of time encoding of digital input data with little, if any, loss of information. Preferably, the analog-to-digital conversion would require no oversampling, thereby allowing ultrawide-bandwidth operation. Further, in order for the methods and systems to be economically practical, they should utilize existing chip-scale circuit technologies.